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Big Data Analytics for Processing Real-time Unstructured Data from CCTV in Traffic Management

机译:大数据分析,用于在交通管理中处理来自CCTV的实时非结构化数据

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摘要

Todays many devices generate data everywhere and anytime. Data grow massively and becomes complex thing that needs to be handled. Unstructured data is one type of big data that is difficult to process and consists of unstable attributes. In traffic management, CCTVs are installed to monitor the specific location in the highway. CCTV generates unstructured data in image and video format. These data are difficult to process due to the complexity of the data. This research proposes to implement big data analytics to process real-time unstructured data from CCTV into knowledge displayed in web dashboard. We implement the YOLO framework with YoloV4 Architecture and COCO dataset for traffic flow counting and detecting illegal parking which is categorized as abnormal situation. Unstructured data from CCTV then transformed into semi-structured format in JSON. Data also can be visualized in real time to facilitate local authority to understand the highway situation. Historical data are stored in the NoSQL database to deep more knowledge such as vehicle traffic pattern. The proposed system requires the ROI drawing line as trigger to count the passing vehicles. These experiments are conducted from open CCTV for traffic online in Bali Tower Public Streaming. The prototype result is able to detect the object with 10 fps.
机译:如今,许多设备随时随地生成数据。数据大量增长,成为需要处理的复杂事物。非结构化数据是大数据的一种类型,难于处理并且由不稳定的属性组成。在交通管理中,安装了闭路电视以监视高速公路中的特定位置。闭路电视以图像和视频格式生成非结构化数据。由于数据的复杂性,这些数据难以处理。这项研究建议实施大数据分析,以将来自CCTV的实时非结构化数据处理为Web仪表板中显示的知识。我们使用YoloV4 Architecture和COCO数据集实现YOLO框架,以对交通流量进行计数并检测被归类为异常情况的非法停车。来自CCTV的非结构化数据随后以JSON转换为半结构化格式。数据也可以实时可视化,以方便地方当局了解高速公路状况。历史数据存储在NoSQL数据库中,以提供更多的知识,例如车辆交通模式。拟议的系统需要ROI绘制线作为触发来计算过往车辆的触发器。这些实验是从开放的CCTV进行的,以在Bali Tower Public Streaming中进行在线流量。原型结果能够以10 fps的速度检测对象。

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